# Safetyops Mcp Server

> Production-ready MCP server for workplace safety knowledge base (Azure AI Search + GPT-4o)

- **Type:** MCP server
- **Install:** `agentstack add mcp-anassijassi-safetyops-mcp-server`
- **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior
- **Seller:** [ANASSIJASSI](https://agentstack.voostack.com/s/anassijassi)
- **Installs:** 0
- **Category:** [Cloud & Infrastructure](https://agentstack.voostack.com/c/cloud-infrastructure)
- **Latest version:** 0.1.0
- **License:** MIT
- **Upstream author:** [ANASSIJASSI](https://github.com/ANASSIJASSI)
- **Source:** https://github.com/ANASSIJASSI/safetyops-mcp-server

## Install

```sh
agentstack add mcp-anassijassi-safetyops-mcp-server
```

Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent.

## About

# SafetyOps MCP Server

> **AI-powered safety incident knowledge base** — plug your industrial accident data into any AI assistant in hours, not months.

[](LICENSE)
[](https://www.python.org/downloads/)
[](https://modelcontextprotocol.io)
[](https://azure.microsoft.com/en-us/products/ai-services/ai-search)

---

## What is this?

A production-ready **MCP (Model Context Protocol) server** that turns your workplace incident database into a RAG-powered AI assistant — compatible with **Copilot Studio, Claude, ChatGPT**, and any MCP-compatible client.

Ask your AI agent:
- *"What corrective actions should we take after a welding fire?"* → structured IMMEDIATE / SHORT TERM / LONG TERM action plan with source citations
- *"How many incidents occurred in the chemical industry last year?"* → statistics with AI-generated insights
- *"What are the main causes of falls at height?"* → RAG answer with document references

**No custom development needed for each AI client** — one server, every AI tool.

---

## Why this is different from Azure AI Search direct connector

| Capability | Azure Search connector | SafetyOps MCP |
|---|---|---|
| Basic Q&A | ✅ | ✅ |
| Document search with filters | ❌ | ✅ `kb_search` |
| Statistics & trends by category | ❌ | ✅ `kb_analyze` |
| Prioritized corrective action plan | ❌ | ✅ `kb_suggest` |
| Custom domain logic & prompts | ❌ | ✅ |
| Works with Claude, ChatGPT, custom agents | ❌ | ✅ |
| Deployable for any client's private data | ❌ | ✅ |

---

## 4 MCP Tools

| Tool | Trigger | What it does |
|---|---|---|
| `kb_search` | "find incidents about...", "list accidents where..." | Hybrid search (BM25 + vector) with OData filters. Returns ranked documents with metadata. |
| `kb_converse` | "why...", "how...", "what causes..." | RAG Q&A — retrieves relevant incidents and generates an answer with `[Document X]` citations. |
| `kb_analyze` | "how many...", "statistics", "breakdown by..." | Faceted aggregations by severity / hazard type / industry. Returns counts, percentages, AI insights. |
| `kb_suggest` | "what should we do?", "corrective actions", "after this incident..." | Finds similar past incidents and generates a **prioritized action plan**: 🚨 IMMEDIATE (24h) / ⚠️ SHORT TERM (1 week) / 📋 LONG TERM — with source citations. |

---

## Architecture

```
┌─────────────────────────────────────────────────────────┐
│               AI Client Layer                           │
│   Copilot Studio │ Claude Desktop │ ChatGPT │ Custom    │
└────────────────────────┬────────────────────────────────┘
                         │  JSON-RPC 2.0 (MCP protocol)
                         ▼
┌─────────────────────────────────────────────────────────┐
│            SafetyOps MCP Server (FastAPI)               │
│                                                         │
│  POST /mcp  ──►  ApiKeyMiddleware                       │
│                       │                                 │
│               ToolRegistry.call()                       │
│          ┌────────────┼────────────┐──────────┐         │
│       kb_search  kb_converse  kb_analyze  kb_suggest    │
└──────────────┬──────────────────────┬───────────────────┘
               │                      │
               ▼                      ▼
    Azure AI Search            Azure OpenAI
    (hybrid retrieval)        (gpt-4o-mini)
    279+ incidents             RAG generation
```

---

## Quick Start

### 1. Clone & install

```bash
git clone https://github.com//safetyops-mcp-server.git
cd safetyops-mcp-server
pip install -e ".[dev]"
```

### 2. Configure Azure credentials

```bash
cp .env.example .env
```

Edit `.env`:

```env
# Azure AI Search
AZURE_SEARCH_ENDPOINT=https://.search.windows.net
AZURE_SEARCH_INDEX=safetyops-kb-v2
AZURE_SEARCH_API_KEY=

# Azure OpenAI
AZURE_OPENAI_ENDPOINT=https://.openai.azure.com/
AZURE_OPENAI_CHAT_DEPLOYMENT=gpt-4o-mini
AZURE_OPENAI_EMBEDDING_DEPLOYMENT=text-embedding-3-large
AZURE_OPENAI_API_KEY=

# MCP Server Auth
MCP_API_KEYS=your-secret-key-here
```

### 3. Start the server

```bash
python -m uvicorn safetyops_mcp.app.main:app --port 8001 --reload
```

### 4. Test it

```bash
# Health check
curl http://localhost:8001/health

# List available tools
curl -X POST http://localhost:8001/mcp \
  -H "Content-Type: application/json" \
  -H "X-API-Key: your-secret-key-here" \
  -d '{"jsonrpc":"2.0","id":1,"method":"tools/list"}'

# Ask for corrective actions
curl -X POST http://localhost:8001/mcp \
  -H "Content-Type: application/json" \
  -H "X-API-Key: your-secret-key-here" \
  -d '{
    "jsonrpc": "2.0", "id": 2, "method": "tools/call",
    "params": {
      "name": "kb_suggest",
      "arguments": {
        "incident_description": "A worker was burned during welding operations",
        "language": "en"
      }
    }
  }'
```

---

## Connect to Copilot Studio

> Connect your Microsoft 365 AI assistant to real incident data in 5 minutes.

1. Open your agent in **Copilot Studio**
2. Go to **Actions / Extensions** → **Model Context Protocol (MCP)**
3. Click **Add existing MCP server**
4. Set the server URL:
   - Local (with Cloudflare Tunnel): `https://.trycloudflare.com/mcp`
   - Production (Azure Web App): `https://.azurewebsites.net/mcp`
5. Authentication:
   - Type: **API key**
   - Header name: `X-API-Key`
   - Value: your `MCP_API_KEYS` value
6. Save → the 4 tools appear automatically

See [docs/copilot-studio.md](docs/copilot-studio.md) for detailed setup.

---

## Connect to Claude Desktop

Add to `~/.claude/claude_desktop_config.json`:

```json
{
  "mcpServers": {
    "safetyops": {
      "url": "https://.azurewebsites.net/mcp",
      "headers": { "X-API-Key": "" }
    }
  }
}
```

---

## Deploy to Production (Azure Web App)

```bash
# Production server
gunicorn -c gunicorn.conf.py safetyops_mcp.app.main:app
```

See [docs/azure-deployment.md](docs/azure-deployment.md) for full Azure App Service setup.

> Never commit `.env`. Use Azure Key Vault in production.

---

## Fully Adaptable to Your Business Needs

The 4 built-in tools are a **starting point**, not a ceiling. Every layer is designed to be modified or extended without touching the MCP core.

### Adapt the existing tools

Each tool has two levers you can tune for your specific context:

**1. Output format** — change how results are presented to match your organization's language and standards:

| Tool | Default output | Example adaptation |
|---|---|---|
| `kb_suggest` | IMMEDIATE / SHORT TERM / LONG TERM | → PDCA cycle (Plan / Do / Check / Act) for ISO 45001 clients |
| `kb_converse` | Free-form answer with [Document X] citations | → Structured report: Context / Root Cause / Recommendation |
| `kb_analyze` | Statistics + AI paragraph | → Executive summary table ready for board presentations |
| `kb_search` | Ranked document list | → Filtered by user role (manager sees aggregates, operator sees full details) |

**2. Content & domain logic** — the system prompts encode your domain expertise:

> The HSE system prompt in `kb_suggest` was designed for industrial safety.
> Swap it for a pharma, nuclear, or maritime prompt and the tool becomes a domain expert in that field — no code change required.

---

### Add custom tools for your business case

The tool registry accepts any new tool in minutes. Examples of tools built for specific clients:

```
kb_report     → Auto-generate a formatted incident report (Word/PDF) from a description
kb_compare    → Compare two incidents side by side and identify common root causes
kb_deadline   → Track corrective action deadlines and flag overdue items
kb_escalate   → Score incident severity and route to the right team automatically
kb_translate  → Deliver the action plan in the local language of the site
```

Adding a tool = one Python file + register it in `registry.py`. The AI client discovers it automatically via `tools/list` — no client-side changes needed.

---

### What this means for your deployment

When we deploy for your organization, the tools are configured for **your** workflows, **your** terminology, and **your** output formats — not a generic template. The architecture makes this fast: customization is configuration, not reengineering.

---

```
safetyops_mcp/
├── app/
│   ├── main.py              # FastAPI entry point + /health
│   ├── auth.py              # API key middleware
│   ├── mcp_router.py        # JSON-RPC 2.0 dispatch (/mcp)
│   └── settings.py          # Pydantic settings
└── mcp/
    ├── jsonrpc.py            # JSON-RPC 2.0 models
    ├── registry.py           # Tool registration + dispatch
    └── tools/
        ├── _openai_client.py # Shared Azure OpenAI factory
        ├── kb_search.py      # Hybrid search tool
        ├── kb_converse.py    # RAG Q&A tool
        ├── kb_analyze.py     # Statistical analysis tool
        └── kb_suggest.py     # Corrective action plan tool

data/
└── accidents.csv             # Source dataset (China industrial accidents)

scripts/
├── normalize_china_data.py   # Data normalization pipeline
└── pipeline_blob_to_search.py # Azure Search indexing pipeline

docs/
├── azure-setup.md
├── azure-deployment.md
├── copilot-studio.md
└── runbook.md
```

---

## Adapt to Your Own Data

This template is designed to be **deployed for any incident knowledge base**:

1. Replace `data/accidents.csv` with your incident dataset
2. Adjust the field mapping in `scripts/normalize_china_data.py`
3. Re-run the indexing pipeline
4. The 4 MCP tools work immediately with your data — no code changes

Supported data sources: CSV, JSON, SQL export, SharePoint lists.

See [docs/azure-setup.md](docs/azure-setup.md) for the indexing guide.

---

## Use Cases & Industries

| Industry | Data source | Key tool |
|---|---|---|
| Manufacturing / HSE | OSHA API, internal SIRH | `kb_suggest` — corrective action plans |
| Nuclear | IRSN, NRC event reports | `kb_converse` — regulatory Q&A |
| Maritime | EMSA, MAIB accident reports | `kb_search` — incident lookup |
| Pharmaceutical | FDA Warning Letters | `kb_analyze` — trend analysis |
| Mining | MSHA USA database | `kb_suggest` + `kb_analyze` |

---

## Tech Stack

| Layer | Technology |
|---|---|
| MCP Server | FastAPI + Uvicorn (Python 3.10+) |
| Knowledge Base | Azure AI Search (hybrid BM25 + vector) |
| LLM | Azure OpenAI gpt-4o-mini |
| Embeddings | text-embedding-3-large |
| AI Client | Copilot Studio, Claude Desktop, ChatGPT |
| Public Exposure | Cloudflare Tunnel (dev) / Azure Web App (prod) |
| Demo UI | Streamlit |

---

## License

MIT — see [LICENSE](LICENSE).

---

*Built with the MCP open standard — works with every AI client today and tomorrow.*

## Source & license

This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [ANASSIJASSI](https://github.com/ANASSIJASSI)
- **Source:** [ANASSIJASSI/safetyops-mcp-server](https://github.com/ANASSIJASSI/safetyops-mcp-server)
- **License:** MIT

Install and usage instructions live in the source repository linked above.

## Pricing

- **Free** — Free

## Security capabilities

Automated source analysis of v0.1.0 — what this tool can access:

- **Network access:** yes
- **Filesystem access:** no
- **Shell / process execution:** no
- **Environment & secrets:** yes
- **Dynamic code execution:** no

*"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.*


## Versions

- **0.1.0** — security scan: passed — Imported from the upstream source.

## Links

- Listing page: https://agentstack.voostack.com/l/mcp-anassijassi-safetyops-mcp-server
- Seller: https://agentstack.voostack.com/s/anassijassi
- Browse the marketplace: https://agentstack.voostack.com/browse

---
Listed on AgentStack — the marketplace for AI agent skills and MCP servers. Every listing is security-reviewed. Creators keep 70%.